Convert inconsistent modeling style to standardized Pydantic models for all
external-facing data structures while maintaining TypedDict compatibility where
appropriate for internal layer-private structures.
Changes:
- Converted IpLookupResult TypedDict to use IpLookupResponse Pydantic model
in jail_service.lookup_ip() for consistency with routers
- Added GeoCacheEntry Pydantic model for geo cache repository rows
- Converted GeoCacheRow TypedDict to use GeoCacheEntry alias
- Converted ImportLogRow TypedDict to use ImportLogEntry alias
- Updated routers and services to work with Pydantic models
- Updated all tests to use Pydantic model field access (attributes)
instead of dict subscripting
Documentation:
- Added 'Model Type Usage by Layer' section to Backend-Development.md
- Defines when TypedDict is allowed (internal structures) vs Pydantic
(external-facing, cross-boundary data)
- Provides clear guidance on modeling conventions per layer
Benefits:
- Consistent validation and serialization behavior
- Better IDE support and type checking
- Clearer separation of concerns by layer
- Reduced maintenance cost from mixed validation approaches
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Add automatic cleanup of stale geolocation cache entries to prevent
unbounded database growth. Resolves the issue where unique IP addresses
accumulated indefinitely in the geo_cache table, degrading query performance.
## Changes
### Database Schema (Migration 3)
- Add 'last_seen' column to geo_cache table tracking last reference time
- Existing entries default to current timestamp
### Repository Layer (geo_cache_repo.py)
- Update upsert_entry() to set/refresh last_seen on insert/update
- Update upsert_neg_entry() to set/refresh last_seen on negative cache hits
- Update bulk_upsert_entries() to set/refresh last_seen in batch operations
- Add delete_stale_entries(db, cutoff_iso) -> int for purging old entries
### Background Task (geo_cache_cleanup.py)
- New APScheduler task that runs nightly (24-hour interval)
- Calculates cutoff as 90 days ago from current time (UTC)
- Deletes all entries with last_seen older than cutoff
- Logs operation results (info when deleted > 0, debug when 0 deleted)
- Configurable retention period via GEO_CACHE_RETENTION_DAYS constant
### Application Startup (startup.py)
- Register geo_cache_cleanup task in scheduler during app startup
- Placed after geo_cache_flush in task registration order
### Tests
- Add delete_stale_entries test cases covering:
* Removal of old entries beyond cutoff
* No deletion when all entries are recent
* Empty table edge case
- Update existing test fixtures to include last_seen column
- Add full test suite for cleanup task registration and execution
### Documentation
- Architekture.md: Document cleanup task, update schema/diagram
- Backend-Development.md: Add retention policy documentation
## Behavior
When an IP is accessed, its last_seen is refreshed. After 90 days of no
access, an IP is purged by the nightly cleanup. On next encounter, the IP
is re-resolved from MaxMind MMDB or ip-api.com (if configured).
This is acceptable because:
1. Stale geolocation data may become inaccurate over time
2. Re-resolution cost is minimal compared to unbounded storage growth
3. Active IPs maintain fresh data through their last_seen updates
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
